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Record W4294842785 · doi:10.1080/00085006.2022.2106699

Zelens′kyi uses his communication skills as a weapon of war

2022· article· en· W4294842785 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Slavonic Papers · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and Russian Geopolitical Military Strategies
Canadian institutionsQueen's UniversityWestern University
Fundersnot available
KeywordsUkrainianDisinformationPolitical scienceFraming (construction)Media studiesNarrativeSociologyLawSocial mediaHistory

Abstract

fetched live from OpenAlex

Ukraine’s President Volodymyr Zelens′kyi’s communication skills have proven to be a powerful weapon against Russia’s disinformation war towards Ukraine. When Russia launched its full-scale military invasion of Ukraine in February 2022, he began recording daily messages to Ukrainian society and reaching out to international audiences through live addresses. This paper analyzes Zelens′kyi’s speeches during the first 50 days of the intensified war. It examines the agenda-setting and framing methods, honed by his television experience, that he used to reach audiences, as well as their content. It suggests that these speeches made Ukraine’s narrative dominant in international media, dispersing the information fog Russia was trying to create whereby Ukraine needed to be “de-Nazified,” neutralized, and kept in Russia’s sphere of influence. They also helped consolidate Ukrainian society and strengthen international assistance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.953
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.253
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it